---------------------------------------------------In the framework of the trade-off between interpretability and accuracy in Linguistic Fuzzy Rule Based Systems, this doctoral thesis is developed using adaptive operators and evolutionary methods to adapt them together with the Rule Base. This work shows the usefulness of the method developed, based on evolutionary adaptive operators, for Fuzzy Modelling designers. Moreover, the thesis shows a model with cooperation between the tow main components of the Fuzzy System: the Inference Mechanism and the Rule Base. This cooperation is reached through the learning of both elements inside a single complex evolutionary model.